agntrick-whatsapp 0.2.0

WhatsApp integration for Agntrick agents

agntrick-whatsapp

WhatsApp integration for Agntrick agents.

Installation

pip install agntrick-whatsapp

Or with the core package:

pip install agntrick[whatsapp]

Features

• WhatsApp Channel: Bidirectional communication via personal WhatsApp account
• Router Agent: Routes messages to different specialist modes based on commands
• Audio Transcription: Transcribe voice messages using Groq Whisper API
• Contact Filtering: Privacy-focused with allowed contacts only

Requirements

System Dependencies

The WhatsApp channel uses neonize which requires:

• libmagic: For file type detection
  • macOS: brew install libmagic
  • Ubuntu/Debian: sudo apt-get install libmagic1
  • Fedora: sudo dnf install file-devel

Audio Transcription (Optional)

For audio transcription, you need:

• ffmpeg: For audio format conversion

  • macOS: brew install ffmpeg
  • Ubuntu/Debian: sudo apt-get install ffmpeg
  • Fedora: sudo dnf install ffmpeg

• Groq API Key: Set GROQ_AUDIO_API_KEY or GROQ_API_KEY environment variable

Quick Start

1. Create Configuration

Create a whatsapp.yaml configuration file:

model: claude-sonnet-4-6
mcp_servers: ["fetch", "web-forager"]

privacy:
  allowed_contact: "[phone]"  # Your phone number

channel:
  storage_path: ~/storage/whatsapp

features:
  text_messages: true
  media_messages: true
  group_messages: false
  typing_indicators: true

audio_transcriber:
  model: whisper-large-v3-turbo
  timeout: 60.0

2. Run the WhatsApp Agent

import asyncio
from agntrick_whatsapp import WhatsAppChannel, WhatsAppRouterAgent
from agntrick_whatsapp.config import WhatsAppAgentConfig

async def main():
    # Load configuration
    config = WhatsAppAgentConfig.model_validate_yaml("whatsapp.yaml")

    # Create channel
    channel = WhatsAppChannel(
        storage_path=config.get_storage_path(),
        allowed_contact=config.privacy.allowed_contact,
    )

    # Create router agent
    agent = WhatsAppRouterAgent(
        channel=channel,
        model_name=config.model,
        mcp_servers_override=config.mcp_servers,
        audio_transcriber_config=config.audio_transcriber,
    )

    # Start listening
    await agent.start()

asyncio.run(main())

Commands

The router agent supports the following commands:

Command	Description
/learn <topic>	Learning/tutorial mode
/youtube <url>	YouTube video analysis
(default)	General assistant mode

Examples

• /learn Python decorators - Get a step-by-step tutorial on Python decorators
• /youtube https://youtube.com/watch?v=xyz - Analyze a YouTube video
• What's the weather in Tokyo? - General question

Audio Transcription

Voice messages are automatically transcribed using Groq's Whisper API:

from agntrick_whatsapp import AudioTranscriber

transcriber = AudioTranscriber()
result = await transcriber.transcribe_audio("/path/to/voice.ogg")
print(result)

Configuration Reference

PrivacyConfig

Field	Type	Required	Description
allowed_contact	str	Yes	Phone number to allow messages from
log_filtered_messages	bool	No	Log filtered messages for debugging

FeatureFlags

Field	Type	Default	Description
text_messages	bool	true	Enable text messages
media_messages	bool	true	Enable media messages
group_messages	bool	false	Enable group messages
presence_updates	bool	true	Enable presence updates
typing_indicators	bool	true	Send typing indicators

AudioTranscriberConfig

Field	Type	Default	Description
model	str	whisper-large-v3-turbo	Groq Whisper model
timeout	float	60.0	Request timeout in seconds
config_file	str?	None	Optional config file path

Troubleshooting

neonize Import Error

RuntimeError: neonize dependency is unavailable

Install system dependencies (libmagic) and reinstall:

brew install libmagic  # macOS
pip install agntrick-whatsapp --force-reinstall

QR Code Not Appearing

1. Check storage path permissions
2. Delete existing session: rm -rf ~/storage/whatsapp
3. Restart the agent

Audio Transcription Fails

1. Verify Groq API key: echo $GROQ_AUDIO_API_KEY
2. Check ffmpeg: ffmpeg -version
3. Check file size (max 25MB)

License

MIT